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      Alteration of epidermal lipid composition as a result of deficiency in the magnesium transporter Nipal4

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          Abstract

          Lipids in the stratum corneum play an important role in the formation of the skin permeability barrier. The causative gene for congenital ichthyosis, NIPAL4, encodes a Mg 2+ transporter and is involved in increases in intracellular Mg 2+ concentrations that depend on keratinocyte differentiation. However, the role of this increased Mg 2+ concentration in skin barrier formation and its effect on the lipid composition of the stratum corneum has remained largely unknown. Therefore, in the present study, we performed a detailed analysis of epidermal lipids in Nipal4 KO mice via TLC and MS. Compared with WT mice, the Nipal4 KO mice showed compositional changes in many ceramide classes (including decreases in ω- O-acylceramides and increases in ω-hydroxy ceramides), together with increases in ω-hydroxy glucosylceramides, triglycerides, and free fatty acids and decreases in ω- O-acyl hydroxy fatty acids containing a linoleic acid. We also found increases in unusual ω- O-acylceramides containing oleic acid or palmitic acid in the KO mice. However, there was little change in levels of cholesterol or protein-bound ceramides. The TLC analysis showed that some unidentified lipids were increased, and the MS analysis showed that these were special ceramides called 1- O-acylceramides. These results suggest that elevated Mg 2+ concentrations in differentiated keratinocytes affect the production of various lipids, resulting in the lipid composition necessary for skin barrier formation.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

            Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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              HISAT: a fast spliced aligner with low memory requirements.

              HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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                Author and article information

                Contributors
                Journal
                J Lipid Res
                J Lipid Res
                Journal of Lipid Research
                American Society for Biochemistry and Molecular Biology
                0022-2275
                1539-7262
                29 April 2024
                June 2024
                29 April 2024
                : 65
                : 6
                : 100550
                Affiliations
                [1]Laboratory of Biochemistry, Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan
                Author notes
                []For correspondence: Akio Kihara; Yusuke Ohno yusuke-ohno@ 123456pharm.hokudai.ac.jp kihara@ 123456pharm.hokudai.ac.jp
                Article
                S0022-2275(24)00055-5 100550
                10.1016/j.jlr.2024.100550
                11153242
                38692573
                51e2c8e8-1bb8-4afb-b4e1-f00b75ec8627
                © 2024 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 2 February 2024
                : 23 April 2024
                Categories
                Research Article

                Biochemistry
                acylceramides,ceramides,lipidomics,lipids,magnesium ion,skin,sphingolipids
                Biochemistry
                acylceramides, ceramides, lipidomics, lipids, magnesium ion, skin, sphingolipids

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